NEURAL-NETWORK APPROACH TO FAULT-DIAGNOSIS IN CMOS OPAMPS WITH GATE OXIDE SHORT FAULTS

被引：17

作者：

YU, S ^{[1
]}

JERVIS, BW ^{[1
]}

ECKERSALL, KR ^{[1
]}

BELL, IM ^{[1
]}

HALL, AG ^{[1
]}

TAYLOR, GE ^{[1
]}

机构：

[1] UNIV HULL,SCH ENGN & COMP,VLSI DESIGN & TEST GRP,KINGSTON HULL HU6 7RX,N HUMBERSIDE,ENGLAND

来源：

ELECTRONICS LETTERS | 1994年 / 30卷 / 09期

关键词：

NEURAL NETWORKS; CMOS INTEGRATED CIRCUITS; INTEGRATED CIRCUIT TESTING; OPERATIONAL AMPLIFIERS;

D O I：

10.1049/el:19940472

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Faults owing to gate oxide shorts in a CMOS opamp have been diagnosed in simulations using artificial neural networks to identify corresponding variations in supply current. Ramp and sinusoidal signals gave fault diagnostic accuracy of 67 and 83%, respectively. Using both test signals 100% diagnostic accuracy was achieved.

引用

页码：695 / 696

页数：2